Preliminary Reading and Graphing of Inspection Data

During the Summer of 2021, data from ICE facility inspections was compiled into a series of spreadsheets. The impetus for the project was Nathan Craig who was interested in collating the data to examine them for trends, patterns, and anomalies. The work was performed by three students funded under a National Science Foundation grant awarded to Dr. Neil Harvey (NMSU) and Dr. Jeremy Slack (NMSU). The students who performed the work were Juan Becerra (Stanford), Avigail Turima Romo (Columbia), and Daniela Navarro Verdugo (CSSLO). The three students worked with Nathan Craig (NMSU and AVID) to develop a workflow for compiling individual report significant incident summary forms and inspection cover letters into a series of spreadsheets.

This document is a preliminary proof of concept and initial exploratory data analysis (Tukey 1977). Goals of the document are to:

• illustrate the kinds of analysis possible with the tabulation of ICE inspection data
• demonstrate code for reading the spreadsheet
• show specific wrangling methods unique to the data structure
• provide preliminary exploratory plot of select variables from the Significant Incident Summary Sheets.

The data are presently incomplete and represent results compiled as of 2021-06-24.

# Load necessary libraries

# Reading and wrangling
library(googlesheets4)
library(readr)
library(tidyverse)
library(janitor)
library(lubridate)
library(DT)

# Plotting
library(ggplot2)
library(RColorBrewer)

# Tables
library(kableExtra)

1 Introduction

1.1 Method for Reading G-324A-19-inc form

The code for this report is specific to data logged in the G-324A-19 form and the incident summaries portion of that form. The incident summary portion of this form is probably the most complex data structure in the project and also contains the largest volume of quantitative information. Therefore, it seemed like a good place to start with an initial proof of concept.

At the outset, there were issues reading in the Google Sheet. Several of the numeric columns read into R as lists which was undesirable. In the Google Sheet, Craig set the columns to plain text rather than auto and the data read in fine as character columns. This seemed to resolve the issue for a time, and it was possible to use the type_convert() function from the readr library (Wickham and Hester 2020) to convert these columns to numbers. Additional steps were taken to use the read_sheet function of the googlesheets4 library (Bryan 2021) to explicitly set the column types to character.

There were also some issues using lubridate (Spinu, Grolemund, and Wickham 2021) to wrangle the month and year fields to a proper date. Craig was not able to discern the cause of the issue. However, changing the month format on the incident sheet from abbreviated to fully written out months solved the issue. Those changes were made in the master Google Sheet and the data were called using the googlesheets4 library.

# Read in Sheet G-324A-19
df_324 <- read_sheet("https://docs.google.com/spreadsheets/d/1im5VSi3bIEi13O8WQ56wEIXSyNEstbGMylXXgD9bAG0/edit#gid=1858227071",
                 sheet="G-324A-19",
                 col_names = TRUE,
                 col_types = "c") %>% 
  clean_names() %>% 

  # Clean up the facility names separating out inspection date and state
  # Note the use of a double escape character. This was necessary.
  separate(.,
           col = facility,
           into = c("facility","inspection_date"),
           sep = "\\) - ") %>%
  separate(.,
           col = facility,
           into = c("facility","state"),
           sep = "\\(") %>% 

  # Convert the character type cols to numbers
  # type_convert() %>%
  mutate(facility = as.factor(facility),
         state = as.factor(state),
         date = mdy(inspection_date),
         current_inspection_date_from = mdy(current_inspection_date_from),
         current_inspection_date_to = mdy(current_inspection_date_to)
         ) %>% 
  relocate(date, .before = inspection_date) %>% 
  mutate_at(c(20:49), as.numeric)

# Read Google Sheet incident worksheet, convert to data frame, and wrangle
df_324_inc <- read_sheet("https://docs.google.com/spreadsheets/d/1im5VSi3bIEi13O8WQ56wEIXSyNEstbGMylXXgD9bAG0/edit#gid=1858227071",
                 sheet="G-324A-19-inc",
                 col_types = "c") %>% 
  clean_names() %>% 

  # Clean up the facility names separating out inspection date and state
  # Note the use of a double escape character. This was necessary.
  separate(.,
           col = facility,
           into = c("facility","inspection_date"),
           sep = "\\) - ") %>%
  separate(.,
           col = facility,
           into = c("facility","state"),
           sep = "\\(") %>% 

  # Convert the character type cols to numbers
  # type_convert() %>% 
  unite(date, year:month) %>% 
  mutate(facility = as.factor(facility),
         state = as.factor(state),
         date = ym(date)
         ) %>% 
  mutate_at(c(6:76), as.numeric)

At present 170 out of approximately 300 are complete. The inspections range in time from 2019-08-22 to 2021-04-08.

1.2 Summary Tables

Summary tables help to provide an overview of how many instances occur within particular category of data or how frequent a particular issue is recorded at a given facility. Summary tables are generated using a combination of group_by with summarize with the results piped to kable and kableExtra.

df_facility <- df_324 %>% 
  group_by(facility) %>% 
  summarise(n_inspections = n()) %>% 
  ungroup() 
  
df_facility %>% 
  kable(caption = "Inspections Reviewed by Facility",
        col.names = c("Facility", "Inspections Reviewed")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 1.1: Inspections Reviewed by Facility

Facility	Inspections Reviewed
Adams County Correctional Center	2
Adelanto ICE Processing Center - East	2
Adelanto ICE Processing Center - West	2
Alamance County Detention Center	1
Alamance County Jail	1
Allen Parish Public Safety Complex	2
Aurora ICE Processing Center	2
Aurora ICE Processing Center II - Annex	2
Baker County Detention Center	1
Bergen County Jail	2
Bluebonnet Detention Center	1
Boone County Jail	2
Bossier Parish Corrections Center	1
Bristol County Jail and House of Correction	1
Brooks County Detention Center	1
Broward Transitional Center	2
Butler County Jail	1
Calhoun County Correctional Center	1
Calhoun County Jail	1
Cambria County Prison	1
Caroline Detention Facility	1
Carver County Jail	1
Cass County Jail	1
Catahoula Correctional Center	2
CCA Florence Correctional Center	1
Chase County Detention Center	1
Chippewa County Correctional Facility	1
Christian County Jail	1
Cibola County Correctional Center	1
Clay County Justice Center	1
Clinton County Correctional Facility	2
Coastal Bend Detention Center	1
David L. Moss Criminal Justice Center	1
Desert View Annex	1
Dodge County Detention Facility	1
Donald W. Wyatt Detention Center	1
Donald W. Wyatt Detention Facility	1
Dorchester County Detention Center	1
Douglas County Department of Corrections	1
East Hidalgo Detention Center	1
Eden Detention Center	1
El Paso Service Processing Center	2
El Valle Detention Facility	1
Elizabeth Contract Detention Facility	2
Eloy Detention Center	2
Essex County Corrections Facility	2
Etowah County Jail	1
Farmville Detention Center	1
Florence SPC	1
Folkston ICE Processing Center	1
Folkston ICE Processing Center Annex	1
Freeborn County Adult Detention Center	1
Geauga County Jail	2
Glades County Detention Center	1
Golden State Annex	1
Hall County Department of Corrections	1
Hardin County Jail	2
Henderson Detention Center	1
Houston CDF	1
Houston Contract Detention Facility	1
Howard County Detention Center	1
Hudson County Corrections and Rehabilitation Center	1
Imperial Regional Detention Facility	2
Irwin County Detention Center	1
Jackson Parish Correctional Center	2
Jena LaSalle Detention Facility	1
Jerome Combs Detention Center	2
Joe Corley Detention Facility	1
Joe Corley Processing Center	1
Johnson County Corrections Center	1
Kay County Detention Center	2
Krome Service Processing Center	2
La Palma Correctional Center	1
Laredo Processing Center	1
LaSalle Correctional Center	1
LaSalle County Regional Detention Center	1
LaSalle ICE Processing Center	1
Limestone County Detention Center	2
McHenry County Adult Correctional Facility	1
Mesa Verde ICE Processing Facility	1
Monroe County Inmate Dormitory	1
Montgomery County Jail	1
Montgomery Processing Center	2
Morgan County Adult Detention Center	1
Morrow County Correctional Facility	1
Northern Oregon Correctional Facility	1
Northwest Contract Detention Center	1
Nye County Detention Center	1
Okmulgee County Jail - Moore Detention Facility	1
Orange County Jail	1
Otay Mesa Detention Facility	2
Otero County Processing Center	2
Pike County Correctional Facility	1
Pine Prairie ICE Processing Center	1
Platte County Detention Center	1
Plymouth County Correctional Facility	1
Polk County Adult Detention Center	2
Port Isabel Service Processing Center	2
Prairieland Detention Center	2
Pulaski County Detention Center	1
Richwood Correctional Center	2
Rio Grande Processing Center	1
River Correctional Center	2
Robert A. Deyton Detention Facility	2
Rolling Plains Detention Center	1
Saint Clair County Jail	1
San Luis Regional Detention Center	1
Seneca County Jail	2
Shawnee County Department of Corrections - Adult Detention Center	1
Sherburne County Jail	2
Sheriff Al Cannon Detention Center	1
South Louisiana ICE Processing Center	2
South Texas ICE Processing Center	1
Stewart Detention Center	1
Strafford County Corrections	2
Teller County Jail	1
Torrance County Detention Facility	1
Tulsa County Jail - David L. Moss Criminal Jutice Center	1
Val Verde Correctional Facility	1
Wakulla County Detention Facility	2
Washoe County Detention Center	1
Webb County Detention Center	1
Webb County Detention Facility	1
West Texas Detention Facility	1
Western Tennessee Detention Facility	1
Willacy County Regional Detention Facility	1
Winn Correctional Center	2
Worcester County Jail	1
York County Prison	2
Yuba County Jail	2

1.3 Facet Plots

Facet plots are produced for several categories of data. Within each category, columns are pivoted longer and plotted by date. Graphing is done using the ggplot2 library (Wickham et al. 2021) with the facet_wrap function to provide a means to compare multiple facilities simultaneously. Such a plot can help identify trends and guide more specific questions.

2 Assaults

The ICE G-324A Significant Incident Summary sheet contains information on a number of different kinds of assaults. Specifically, there are four categories of assaults listed:

• Detained Person on Staff with Serious Injury
• Detained Person on Staff without Serious Injury
• Detained Person on Detained Person with Serious Injury
• Detained Person on Detained Person without Serious Injury

Conspicuously absent from this list of assault types are assaults on detained persons by staff. This is deeply concerning because already initial review of inspection forms and prior news stories indicates that staff assaults on detained persons do occur. For example, at the Bristol County County Jail and House of Corrections independent investigation by the Massachusetts Office of Attorney General (MAOG) found that facility staff found a “planned and deliberate-use of force against the ICE detainees that was disproportionate to the security needs at that time and unnecessarily caused, or risked causing, harm to all involved” (MA AG 2020, ii). The MOAG found that facility staff used “a flash bang grenade, pepper-ball launchers, pepper spray canisters, anti-riot shields, and canines–against detainees who had exhibited calm and nonviolent behavior for at least an hour before this operation” (MA AG 2020, ii). Investigations found that staff “deployed these weapons both indiscriminately upon entry and also specifically against detainees who were not combative, assaultive, or otherwise actively resisting staff” (MA AG 2020, ii).

While the aforementioned Bristol County Jail may be a particularly egregious instance of staff assaulting detained persons, it is not an isolated case. For example, video evidence from the Torrance County Detention Facility in Estancia NM shows CoreCivic’s private facility staff pepper spraying persons detained by ICE on hunger strike (Swetlitz 2020). Review of inspections has also revealed additional inappropriate use of force incidents. The omission of a field to record instances of staff assaulting detained persons occludes and obscures real instances of violence. As the inspections process is a detention reform designed to make a more humane system of civil incarceration, the omission of categories for logging staff physical mistreatment of detained persons raises serious questions about the inspections processes ability to record significant and documented civil and human rights violations.

2.1 Summary Tables

df_assaults <- df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       detainee_physical_assault_on_staff_with_serious_injury:
       detainee_on_detainee_physical_assault_fight_with_no_serious_injury
       ) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create a new total column
  mutate(total_assaults = sum(c_across(
       detainee_physical_assault_on_staff_with_serious_injury:
       detainee_on_detainee_physical_assault_fight_with_no_serious_injury
  ))) %>% 

  # Call a range of table columns and pivot long
  pivot_longer(.,
               cols=  detainee_physical_assault_on_staff_with_serious_injury:total_assaults,
               names_to = "assault_type",
               values_to = "assault_count") %>% 
  
  # Remove NA Values
  drop_na() %>% 
  
  # Explicitly define factor levels
  mutate(assault_type = factor(assault_type, levels = c(
    "detainee_physical_assault_on_staff_with_serious_injury",
    "detainee_physical_assault_on_staff_with_no_serious_injury",
    "detainee_on_detainee_physical_assault_fight_with_serious_injury",
    "detainee_on_detainee_physical_assault_fight_with_no_serious_injury",
    "total_assaults"
  )))

df_assaults %>% 
  group_by(assault_type) %>% 
  summarise(`Total Assaults by Type` = sum(assault_count)) %>% 
  ungroup() %>% 
  kable(caption = "Total Assaults by Type",
        col.names = c("Assault Type", "Total Assault Type")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive"))

Table 2.1: Total Assaults by Type

Assault Type	Total Assault Type
detainee_physical_assault_on_staff_with_serious_injury	12
detainee_physical_assault_on_staff_with_no_serious_injury	311
detainee_on_detainee_physical_assault_fight_with_serious_injury	123
detainee_on_detainee_physical_assault_fight_with_no_serious_injury	2795
total_assaults	3233

df_assaults %>% 
  group_by(facility) %>% 
  summarise(total_assaults = sum(assault_count)) %>% 
  arrange(desc(total_assaults)) %>% 
  ungroup() %>% 
  kable(caption = "Total Assaults by Facility",
        col.names = c("Facility", "Total Assaults by Facility")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 2.1: Total Assaults by Facility

Facility	Total Assaults by Facility
Krome Service Processing Center	470
Adelanto ICE Processing Center - West	390
Prairieland Detention Center	330
South Texas ICE Processing Center	312
Adelanto ICE Processing Center - East	264
Otero County Processing Center	240
Aurora ICE Processing Center	222
Aurora ICE Processing Center II - Annex	222
Eloy Detention Center	216
Stewart Detention Center	206
Otay Mesa Detention Facility	200
El Paso Service Processing Center	192
Winn Correctional Center	172
Imperial Regional Detention Facility	136
LaSalle ICE Processing Center	128
Farmville Detention Center	108
Hudson County Corrections and Rehabilitation Center	98
Jena LaSalle Detention Facility	98
River Correctional Center	96
Yuba County Jail	96
Adams County Correctional Center	94
La Palma Correctional Center	92
Caroline Detention Facility	90
Essex County Correctional Facility	90
Catahoula Correctional Center	72
Mesa Verde ICE Processing Facility	72
Northwest Contract Detention Center	72
Port Isabel Service Processing Center	70
Folkston ICE Processing Center	68
Bluebonnet Detention Center	64
Montgomery Processing Center	60
Sherburne County Jail	60
Essex County Corrections Facility	56
Bergen County Jail	52
Pine Prairie ICE Processing Center	52
Limestone County Detention Center	50
Polk County Adult Detention Center	50
Irwin County Detention Center	48
McHenry County Adult Correctional Facility	48
Strafford County Corrections	46
Allen Parish Public Safety Complex	45
Baker County Detention Center	34
Elizabeth Contract Detention Facility	34
Houston Contract Detention Facility	32
CCA Florence Correctional Center	30
Pike County Correctional Facility	30
Wakulla County Detention Facility	30
Johnson County Corrections Center	28
Tulsa County Jail - David L. Moss Criminal Jutice Center	28
Houston CDF	26
Richwood Correctional Center	26
Bossier Parish Corrections Center	24
Folkston ICE Processing Center Annex	24
Okmulgee County Jail - Moore Detention Facility	24
Pulaski County Detention Center	24
Clinton County Correctional Facility	22
Jackson Parish Correctional Center	22
Nye County Detention Center	22
Bristol County Jail and House of Correction	20
Joe Corley Processing Center	20
Morgan County Adult Detention Center	20
Orange County Jail	20
Plymouth County Correctional Facility	20
Cambria County Prison	18
Freeborn County Adult Detention Center	18
Glades County Detention Center	16
Hall County Department of Corrections	16
Webb County Detention Center	16
Webb County Detention Facility	16
York County Prison	16
Calhoun County Correctional Center	14
Florence SPC	14
Henderson Detention Center	14
Seneca County Jail	14
Broward Transitional Center	12
Butler County Jail	12
Hardin County Jail	12
Torrance County Detention Facility	12
Coastal Bend Detention Center	10
Dodge County Detention Facility	10
Eden Detention Center	10
El Valle Detention Facility	10
Howard County Detention Center	10
Joe Corley Detention Facility	10
Sheriff Al Cannon Detention Center	8
Worcester County Jail	7
Donald W. Wyatt Detention Center	6
Geauga County Jail	6
Jerome Combs Detention Center	6
Kay County Detention Center	6
Montgomery County Jail	6
Saint Clair County Jail	6
Val Verde Correctional Facility	6
Northern Oregon Correctional Facility	4
San Luis Regional Detention Center	4
Boone County Jail	2
Carver County Jail	2
Cass County Jail	2
Clay County Justice Center	2
Laredo Processing Center	2
Monroe County Inmate Dormitory	2
Rolling Plains Detention Center	2
Shawnee County Department of Corrections - Adult Detention Center	2
South Louisiana ICE Processing Center	2
Teller County Jail	2
West Texas Detention Facility	2
Alamance County Detention Center	0
Brooks County Detention Center	0
Christian County Jail	0
Cibola County Correctional Center	0
David L. Moss Criminal Justice Center	0
Douglas County Department of Corrections	0
East Hidalgo Detention Center	0
Golden State Annex	0
LaSalle Correctional Center	0
LaSalle County Regional Detention Center	0
Morrow County Correctional Facility	0
Platte County Detention Center	0
Rio Grande Processing Center	0
Robert A. Deyton Detention Facility	0
Washoe County Detention Center	0
Western Tennessee Detention Facility	0
Willacy County Regional Detention Facility	0

2.2 Facet of Assaults by Plot

The figure below is a facet plot of the assault categories present on the G-324A SIS form.

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid",
    "solid",
    "solid",
    "dotted"
    )

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(5, "Paired")
plot_colors[5] <- "#000000"

# Create the labels
plot_labels <- c(
    "Detained Person on Staff w. Serious Injury",
    "Detained Person on Staff w/o Serious Injury",
    "Detained Person on Detained Person w. Serous Injury",
    "Detained Person on Detained Person w/o Serous Injury",
    "Total Assaults")

df_assaults %>% 
  # Calling the plot and formatting
  ggplot(aes(x=date, y = assault_count, linetype=assault_type))+
  geom_line(aes(color = assault_type), size =.65) +
  
  # Set the line type
  scale_linetype_manual(
    values = plot_lines,
    labels = plot_labels,
    name = "Assault Type:",
    guide = guide_legend(nrow = 5)
    )+
  
  # Setting the color
  scale_color_manual(
    values = plot_colors,
    labels = plot_labels,
  name = "Assault Type:"
  )+

  labs(title = "Reported Assaults")+
  ylab("Number of Assaults")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+

  # Set the legend to multiple rows
  guides(col = guide_legend(nrow =5))+
  
  # Wrap
  facet_wrap(~ facility, ncol=3)

3 Disciplinary

As a matter of law, ICE detention is not punitive it is purely administrative civil holding to ensure that individuals are present for their immigration proceedings. Despite that fact, there is a tremendous amount of punitive disciplinary measures that take place in ICE detention. Some of this information on discipline in ICE detention is logged in facility inspections. As seen in the tables below, during the current sample period there were more than 42,000 disciplinary infractions.

3.1 Summary Tables

df_discipline <- df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       disciplinary_infractions:
       sanctions_over_60_days
       ) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create a new total column
  mutate(total_disciplinary = sum(c_across(
       disciplinary_infractions:
       sanctions_over_60_days
  ))) %>% 

  # Call a range of table columns and pivot long
  pivot_longer(.,
               cols=  disciplinary_infractions:total_disciplinary,
               names_to = "disciplinary_type",
               values_to = "disciplinary_count") %>%
  
  # Remove NA values
  drop_na() %>% 
  
  # Explicitly set factor levels
  mutate(disciplinary_type = factor(disciplinary_type, levels =c(
    "disciplinary_infractions",
    "disciplinary_infractions_guilty",
    "disciplinary_appeals",
    "disciplinary_appeals_found_in_favor_of_detainee",
    "sanctions_over_60_days",
    "total_disciplinary"
  )))

df_discipline %>% 
  group_by(disciplinary_type) %>% 
  summarise(`Total Disciplinary by Type` = sum(disciplinary_count)) %>% 
  ungroup() %>% 
  kable(caption = "Total Disciplinary by Type",
        col.names = c("Discipline Type", "Total Discipline Type")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive"))

Table 3.1: Total Disciplinary by Type

Discipline Type	Total Discipline Type
disciplinary_infractions	23396
disciplinary_infractions_guilty	18274
disciplinary_appeals	1093
disciplinary_appeals_found_in_favor_of_detainee	281
sanctions_over_60_days	30
total_disciplinary	42363

df_discipline %>% 
  group_by(facility) %>% 
  summarise(total_disciplinary = sum(disciplinary_count)) %>% 
  arrange(desc(total_disciplinary)) %>% 
  ungroup() %>% 
  kable(caption = "Total Discipline by Facility",
        col.names = c("Facility", "Total Discipline by Facility")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 3.1: Total Discipline by Facility

Facility	Total Discipline by Facility
Eloy Detention Center	7128
La Palma Correctional Center	6954
Krome Service Processing Center	4888
Sherburne County Jail	4070
Farmville Detention Center	3808
Yuba County Jail	3712
Aurora ICE Processing Center	2678
Aurora ICE Processing Center II - Annex	2678
Otay Mesa Detention Facility	2504
Stewart Detention Center	2268
Winn Correctional Center	2264
Montgomery Processing Center	2060
Bluebonnet Detention Center	1926
Otero County Processing Center	1924
South Texas ICE Processing Center	1912
Prairieland Detention Center	1596
Adelanto ICE Processing Center - West	1284
El Paso Service Processing Center	1246
Imperial Regional Detention Facility	1240
Jena LaSalle Detention Facility	1234
LaSalle ICE Processing Center	1176
Clinton County Correctional Facility	1166
Caroline Detention Facility	1116
Bristol County Jail and House of Correction	1048
Polk County Adult Detention Center	1010
Bergen County Jail	984
Northwest Contract Detention Center	958
Essex County Corrections Facility	900
Port Isabel Service Processing Center	848
Calhoun County Correctional Center	836
Glades County Detention Center	822
Folkston ICE Processing Center	814
River Correctional Center	810
McHenry County Adult Correctional Facility	796
Adams County Correctional Center	756
Adelanto ICE Processing Center - East	742
Laredo Processing Center	684
Irwin County Detention Center	680
York County Prison	586
Butler County Jail	566
Folkston ICE Processing Center Annex	502
Tulsa County Jail - David L. Moss Criminal Jutice Center	498
Mesa Verde ICE Processing Facility	482
Pike County Correctional Facility	464
Pine Prairie ICE Processing Center	448
Torrance County Detention Facility	420
Essex County Correctional Facility	404
Strafford County Corrections	400
Hudson County Corrections and Rehabilitation Center	376
Dodge County Detention Facility	352
Pulaski County Detention Center	346
Freeborn County Adult Detention Center	312
Orange County Jail	298
Plymouth County Correctional Facility	252
Houston CDF	240
Houston Contract Detention Facility	240
Jackson Parish Correctional Center	234
Eden Detention Center	230
Baker County Detention Center	216
Johnson County Corrections Center	204
CCA Florence Correctional Center	186
Limestone County Detention Center	176
Okmulgee County Jail - Moore Detention Facility	176
Webb County Detention Facility	174
Florence SPC	168
Broward Transitional Center	166
Joe Corley Detention Facility	164
Allen Parish Public Safety Complex	158
Elizabeth Contract Detention Facility	152
Webb County Detention Center	148
Kay County Detention Center	144
Henderson Detention Center	136
Hardin County Jail	132
Wakulla County Detention Facility	128
Donald W. Wyatt Detention Center	126
Worcester County Jail	125
El Valle Detention Facility	124
Jerome Combs Detention Center	122
Catahoula Correctional Center	88
Geauga County Jail	88
Bossier Parish Corrections Center	80
Montgomery County Jail	80
Nye County Detention Center	76
Hall County Department of Corrections	66
Cambria County Prison	64
Seneca County Jail	62
Howard County Detention Center	54
Joe Corley Processing Center	50
Cibola County Correctional Center	48
Cass County Jail	40
Coastal Bend Detention Center	40
Morgan County Adult Detention Center	40
Washoe County Detention Center	40
Richwood Correctional Center	28
South Louisiana ICE Processing Center	28
Sheriff Al Cannon Detention Center	24
Carver County Jail	22
Saint Clair County Jail	20
Northern Oregon Correctional Facility	18
Shawnee County Department of Corrections - Adult Detention Center	18
Rio Grande Processing Center	16
Rolling Plains Detention Center	12
Christian County Jail	8
Monroe County Inmate Dormitory	8
San Luis Regional Detention Center	8
Teller County Jail	8
West Texas Detention Facility	8
Alamance County Detention Center	0
Boone County Jail	0
Brooks County Detention Center	0
Clay County Justice Center	0
David L. Moss Criminal Justice Center	0
East Hidalgo Detention Center	0
Golden State Annex	0
LaSalle Correctional Center	0
LaSalle County Regional Detention Center	0
Morrow County Correctional Facility	0
Platte County Detention Center	0
Robert A. Deyton Detention Facility	0
Val Verde Correctional Facility	0
Western Tennessee Detention Facility	0
Willacy County Regional Detention Facility	0

3.2 Facet Plot of Disciplinary by Facility

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid",
    "solid",
    "solid",
    "solid",
    "dotted"
    )

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(6, "Paired")
plot_colors[6] <- "#000000"

# Create plot labels

plot_labels <- c(
    "Disciplinary Infractions",
    "Disciplinary Infractions - Guilty",
    "Disciplinary Appeals",
    "Disciplinary Appeals in Favor of Detainee",
    "Sanctions Over 60 Days",
    "Total Disciplinary")


df_discipline %>% 
  
  # Calling the plot and formatting
  ggplot(aes(x=date,
             y = disciplinary_count,
             linetype = disciplinary_type))+
  geom_line(aes(color = disciplinary_type), size = .65) +
  
  # Set the linetype
  scale_linetype_manual(
    values = plot_lines,
    labels = plot_labels,
    name = "Disciplinary Type:",
    guide = guide_legend(nrow = 6)
    )+
  
  # Setting the color
  scale_color_manual(
  values = plot_colors,
  labels = plot_labels,
  name = "Disciplinary Type:"
  )+

  labs(title = "Disciplinary")+
  ylab("Number of Disciplinary Infractions")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+

  # Set the legend to multiple rows
  guides(col = guide_legend(nrow =6))+
  
  # Wrap
  facet_wrap(~ facility, ncol=3)

4 Solitary

4.1 Summary Tables

Of the present 163 inspections reviewed so far, there are more than 34,000 instances of solitary. That is roughly 208 instances of solitary per inspection.

df_solitary <- df_324_inc %>%
  
  # Select a subset of columns to work with
  select(id,
         facility,
         date,
         detainees_placed_in_administrative_segregation:
           detainees_placed_in_segregation_for_mental_health_reasons) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create new total column
  mutate(total_segregation = sum(c_across(detainees_placed_in_administrative_segregation:
                 detainees_placed_in_segregation_for_mental_health_reasons))) %>% 
  
  # Tidy
  pivot_longer(.,
               cols= detainees_placed_in_administrative_segregation:
                 total_segregation,
               names_to = "segregation_type",
               values_to = "segregation_count") %>% 
  
  # Remove NA
  drop_na() %>% 
  
  # Explicitly set factor levels
  mutate(segregation_type = factor(segregation_type, levels = c(
    "detainees_placed_in_administrative_segregation",
    "detainees_placed_in_disciplinary_segregation",
    "detainees_placed_in_segregation_for_medical_reasons",
    "detainees_placed_in_segregation_for_mental_health_reasons",
    "total_segregation"
  )))

df_solitary %>% 
  group_by(segregation_type) %>% 
  summarise(`Total Solitary by Type` = sum(segregation_count)) %>% 
  ungroup() %>% 
  kable(caption = "Total Solitary by Type",
        col.names = c("Solitary Type", "Total Solitary Type")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive"))

Table 4.1: Total Solitary by Type

Solitary Type	Total Solitary Type
detainees_placed_in_administrative_segregation	15798
detainees_placed_in_disciplinary_segregation	8885
detainees_placed_in_segregation_for_medical_reasons	8545
detainees_placed_in_segregation_for_mental_health_reasons	880
total_segregation	33785

df_solitary %>% 
  group_by(facility) %>% 
  summarise(total_segregation = sum(segregation_count)) %>% 
  arrange(desc(total_segregation)) %>% 
  ungroup() %>% 
  kable(caption = "Total Solitary by Facility",
        col.names = c("Facility", "Total Solitary by Facility")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 4.1: Total Solitary by Facility

Facility	Total Solitary by Facility
Krome Service Processing Center	10882
Eloy Detention Center	4556
El Paso Service Processing Center	3310
Prairieland Detention Center	2788
Henderson Detention Center	2638
Winn Correctional Center	2474
Otero County Processing Center	2332
La Palma Correctional Center	2198
Adelanto ICE Processing Center - West	2178
Irwin County Detention Center	2172
South Texas ICE Processing Center	1696
Adams County Correctional Center	1456
River Correctional Center	1438
York County Prison	1418
Montgomery Processing Center	1324
Adelanto ICE Processing Center - East	1308
Otay Mesa Detention Facility	1266
Caroline Detention Facility	1250
Jackson Parish Correctional Center	1248
Aurora ICE Processing Center	1138
Aurora ICE Processing Center II - Annex	1138
Farmville Detention Center	1006
Imperial Regional Detention Facility	1006
Glades County Detention Center	974
Northwest Contract Detention Center	946
Port Isabel Service Processing Center	932
LaSalle ICE Processing Center	928
Sherburne County Jail	796
Catahoula Correctional Center	662
Stewart Detention Center	610
Jena LaSalle Detention Facility	602
Pike County Correctional Facility	598
Pine Prairie ICE Processing Center	472
McHenry County Adult Correctional Facility	462
Bluebonnet Detention Center	452
Baker County Detention Center	362
Wakulla County Detention Facility	342
Bristol County Jail and House of Correction	336
Polk County Adult Detention Center	296
Pulaski County Detention Center	276
Richwood Correctional Center	256
Florence SPC	234
Yuba County Jail	224
Bergen County Jail	218
Limestone County Detention Center	206
Clinton County Correctional Facility	196
Houston Contract Detention Facility	194
Houston CDF	178
Plymouth County Correctional Facility	176
Hudson County Corrections and Rehabilitation Center	174
El Valle Detention Facility	172
Freeborn County Adult Detention Center	172
Geauga County Jail	150
Allen Parish Public Safety Complex	142
LaSalle Correctional Center	140
Okmulgee County Jail - Moore Detention Facility	140
Johnson County Corrections Center	136
Saint Clair County Jail	134
Elizabeth Contract Detention Facility	132
Folkston ICE Processing Center	126
Essex County Correctional Facility	125
Dodge County Detention Facility	118
Joe Corley Detention Facility	110
Mesa Verde ICE Processing Facility	108
Calhoun County Correctional Center	106
Seneca County Jail	102
Kay County Detention Center	92
Nye County Detention Center	92
Donald W. Wyatt Detention Center	88
Essex County Corrections Facility	88
Jerome Combs Detention Center	88
Worcester County Jail	82
Eden Detention Center	78
Butler County Jail	72
Torrance County Detention Facility	58
Hardin County Jail	56
Bossier Parish Corrections Center	54
Tulsa County Jail - David L. Moss Criminal Jutice Center	46
Cambria County Prison	44
Montgomery County Jail	42
Strafford County Corrections	42
Washoe County Detention Center	42
Hall County Department of Corrections	40
Clay County Justice Center	36
CCA Florence Correctional Center	34
Webb County Detention Center	34
Cibola County Correctional Center	32
Folkston ICE Processing Center Annex	24
Cass County Jail	20
Morgan County Adult Detention Center	20
Webb County Detention Facility	20
Alamance County Detention Center	16
Laredo Processing Center	14
Northern Oregon Correctional Facility	14
Sheriff Al Cannon Detention Center	14
Carver County Jail	10
Howard County Detention Center	10
Joe Corley Processing Center	10
Boone County Jail	8
Orange County Jail	8
Golden State Annex	6
Shawnee County Department of Corrections - Adult Detention Center	6
Teller County Jail	6
Christian County Jail	4
Rolling Plains Detention Center	4
San Luis Regional Detention Center	4
Brooks County Detention Center	0
Broward Transitional Center	0
Coastal Bend Detention Center	0
David L. Moss Criminal Justice Center	0
Douglas County Department of Corrections	0
East Hidalgo Detention Center	0
LaSalle County Regional Detention Center	0
Monroe County Inmate Dormitory	0
Morrow County Correctional Facility	0
Platte County Detention Center	0
Rio Grande Processing Center	0
Robert A. Deyton Detention Facility	0
South Louisiana ICE Processing Center	0
Val Verde Correctional Facility	0
West Texas Detention Facility	0
Western Tennessee Detention Facility	0
Willacy County Regional Detention Facility	0

4.2 Facet Plots of Solitary by Facility

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid",
    "solid",
    "solid",
    "dotted"
    )

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(5, "Paired")
plot_colors[5] <- "#000000"

# Create plot labels
plot_labels <- c(
    "Administrative",
    "Disciplinary",
    "Medical",
    "Mental Health",
    "Total")

df_solitary %>% 

# Calling the plot and formatting
  ggplot(aes(x=date,
             y = segregation_count,
             linetype = segregation_type))+
  geom_line(aes(color = segregation_type), size = .65) +
  
  # Set the color
  scale_color_manual(
  values = plot_colors,
  name = "Solitary Type:",
  labels = plot_labels)+
  
  # Set the linetype
  scale_linetype_manual(
    values = plot_lines,
      name = "Solitary Type:",
    labels = plot_labels)+
  
  
  labs(title = "Reported Use of Solitary")+
  ylab("Number of Individuals Palced in Solitary")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+
    facet_wrap(~ facility, ncol=3)

4.3 Solitary Over 60 Days

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(5, "Paired")
plot_colors[5] <- "#000000"

# Call the dataframe and select cols
df_324 %>% 
  select(id,
         facility,
         state,
         date,
         fac_operator,
         admin_seg_60_ice,
         disc_seg_60_ice) %>% 
  drop_na() %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Generate total col
  mutate(total_seg_60 = sum(c_across(
       admin_seg_60_ice:
       disc_seg_60_ice
  ))) %>%
  
  # Make tidy and filter
  pivot_longer(cols = admin_seg_60_ice:disc_seg_60_ice,
               names_to = "segregation_60_type",
               values_to = "segregation_60_count") %>%
  filter(segregation_60_type %in% c("admin_seg_60_ice", "disc_seg_60_ice")&
           segregation_60_count > 0) %>%
  
  # Initiate the plot and sort by sum
  ggplot(aes(x = segregation_60_count,
             y=reorder(fac_operator, segregation_60_count, sum),
             fill=segregation_60_type))+
  geom_bar(stat = "identity")+
  
  # Set the color fill
  scale_fill_brewer(type = "qual",
                    palette = "Paired",
                    name = "Segregation > 60 Type",
                    labels = c("Administrative",
                               "Disciplinary"))+
  labs(title= "Segregation > 60 Days by Facility Operator",
        x = "Segregation > 60 Days Count",
        y = "Facility Operator")+
  theme(legend.position = "bottom")

5 Use of Force

5.1 Summary Tables

df_force <- df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       immediate_use_of_force_incidents:
       strip_searches
       ) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create a new total column
  mutate(total_use_of_force = sum(c_across(
       immediate_use_of_force_incidents:
       strip_searches
  ))) %>% 

  # Call a range of table columns and pivot long
  pivot_longer(.,
               cols=  immediate_use_of_force_incidents:total_use_of_force,
               names_to = "use_of_force_type",
               values_to = "use_of_force_count") %>%
  
  # Remove NA values
  drop_na() %>% 
  
  # Explicitly define factors
  mutate(use_of_force_type = factor(use_of_force_type, levels = c(
    "immediate_use_of_force_incidents",
    "calculated_use_of_force_incidents",
    "uses_of_force_with_chemical_agents",
    "incidents_where_non_lethal_weapons_were_used",
    "number_of_times_4_5_point_restraints_were_used",
    "use_of_force_with_serious_injury",
    "strip_searches",
    "total_use_of_force"
  )))

df_force %>% 
  group_by(use_of_force_type) %>% 
  summarise(`Total Use of Force by Type` = sum(use_of_force_count)) %>% 
  ungroup() %>% 
  kable(caption = "Total Use of Force by Type",
        col.names = c("Use of Force Type", "Total Use of Force Type")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive"))

Table 5.1: Total Use of Force by Type

Use of Force Type	Total Use of Force Type
immediate_use_of_force_incidents	1106
calculated_use_of_force_incidents	311
uses_of_force_with_chemical_agents	333
incidents_where_non_lethal_weapons_were_used	16
number_of_times_4_5_point_restraints_were_used	76
use_of_force_with_serious_injury	2
strip_searches	20297
total_use_of_force	18694

df_force %>% 
  group_by(facility) %>% 
  summarise(total_use_of_force = sum(use_of_force_count)) %>% 
  arrange(desc(total_use_of_force)) %>% 
  ungroup() %>% 
  kable(caption = "Total Use of Force by Facility",
        col.names = c("Facility", "Total Use of Force by Facility")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 5.1: Total Use of Force by Facility

Facility	Total Use of Force by Facility
Farmville Detention Center	10782
La Palma Correctional Center	6022
Sheriff Al Cannon Detention Center	4854
Worcester County Jail	3348
Hudson County Corrections and Rehabilitation Center	2294
York County Prison	2017
Cambria County Prison	1500
Essex County Correctional Facility	1456
Essex County Corrections Facility	1164
Pike County Correctional Facility	1114
Hall County Department of Corrections	916
Northern Oregon Correctional Facility	862
Eloy Detention Center	496
Teller County Jail	484
South Texas ICE Processing Center	254
Port Isabel Service Processing Center	234
Adelanto ICE Processing Center - West	164
Calhoun County Correctional Center	152
Sherburne County Jail	150
Northwest Contract Detention Center	132
Bristol County Jail and House of Correction	130
Glades County Detention Center	126
Folkston ICE Processing Center	122
Otay Mesa Detention Facility	120
Stewart Detention Center	118
Montgomery Processing Center	116
LaSalle ICE Processing Center	112
Bergen County Jail	110
Krome Service Processing Center	80
Aurora ICE Processing Center	66
Aurora ICE Processing Center II - Annex	66
El Paso Service Processing Center	66
Jena LaSalle Detention Facility	66
Mesa Verde ICE Processing Facility	60
Baker County Detention Center	58
Wakulla County Detention Facility	54
River Correctional Center	50
McHenry County Adult Correctional Facility	46
Irwin County Detention Center	42
Limestone County Detention Center	40
Pine Prairie ICE Processing Center	40
Prairieland Detention Center	40
Imperial Regional Detention Facility	38
Winn Correctional Center	36
Strafford County Corrections	33
Bluebonnet Detention Center	32
Donald W. Wyatt Detention Center	28
Johnson County Corrections Center	28
Adelanto ICE Processing Center - East	26
Caroline Detention Facility	26
Jackson Parish Correctional Center	26
Okmulgee County Jail - Moore Detention Facility	24
Morrow County Correctional Facility	22
Pulaski County Detention Center	22
Catahoula Correctional Center	20
Polk County Adult Detention Center	20
Otero County Processing Center	18
Yuba County Jail	18
CCA Florence Correctional Center	16
Plymouth County Correctional Facility	16
Shawnee County Department of Corrections - Adult Detention Center	16
Torrance County Detention Facility	16
Butler County Jail	14
Dodge County Detention Facility	14
Houston CDF	14
Orange County Jail	14
Adams County Correctional Center	12
Eden Detention Center	12
Elizabeth Contract Detention Facility	12
Tulsa County Jail - David L. Moss Criminal Jutice Center	12
Webb County Detention Center	12
Bossier Parish Corrections Center	10
Houston Contract Detention Facility	10
Boone County Jail	8
Broward Transitional Center	8
Clinton County Correctional Facility	8
Joe Corley Detention Facility	8
Nye County Detention Center	6
Richwood Correctional Center	6
Val Verde Correctional Facility	6
Folkston ICE Processing Center Annex	4
Hardin County Jail	4
Henderson Detention Center	4
Joe Corley Processing Center	4
Morgan County Adult Detention Center	4
Seneca County Jail	4
South Louisiana ICE Processing Center	4
Allen Parish Public Safety Complex	2
El Valle Detention Facility	2
Florence SPC	2
Freeborn County Adult Detention Center	2
Geauga County Jail	2
Howard County Detention Center	2
Kay County Detention Center	2
Rolling Plains Detention Center	2
Cass County Jail	1
Alamance County Detention Center	0
Brooks County Detention Center	0
Carver County Jail	0
Christian County Jail	0
Cibola County Correctional Center	0
Clay County Justice Center	0
Coastal Bend Detention Center	0
David L. Moss Criminal Justice Center	0
Douglas County Department of Corrections	0
East Hidalgo Detention Center	0
Golden State Annex	0
Jerome Combs Detention Center	0
Laredo Processing Center	0
LaSalle Correctional Center	0
LaSalle County Regional Detention Center	0
Monroe County Inmate Dormitory	0
Montgomery County Jail	0
Platte County Detention Center	0
Rio Grande Processing Center	0
Robert A. Deyton Detention Facility	0
Saint Clair County Jail	0
San Luis Regional Detention Center	0
Washoe County Detention Center	0
Webb County Detention Facility	0
West Texas Detention Facility	0
Western Tennessee Detention Facility	0
Willacy County Regional Detention Facility	0

5.2 Facet Plot of Use of Force by Facility

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid",
    "solid",
    "solid",
    "solid",
    "solid",
    "solid",
    "dotted"
    )

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(8, "Paired")
plot_colors[8] <- "#000000"

# Create plot labels
plot_labels <- c(
    "Immediate Use of Force Incidents",
    "Calculated Use of Force Incidents",
    "Uses of Force with Chemical Agents",
    "Incidents Where Non-Lethal Weapons Were Used",
    "Times 4/5 Point Restraints Used",
    "Use of Force With Serious Injury",
    "Strip Searches",
    "Total Disciplinary")

df_force %>% 
  
  # Calling the plot and formatting
  ggplot(aes(x=date, y = use_of_force_count, linetype=use_of_force_type))+
  geom_line(aes(color = use_of_force_type), size = .65) +
  
  # setting the linetype
  scale_linetype_manual(
    values = plot_lines,
    labels = plot_labels,
    name = "Use of Force Type:",
    guide = guide_legend(nrow = 8)
    )+
  
  # Setting the color
  scale_color_manual(
  values = plot_colors,
  labels = plot_labels,
  name = "Use of Force Type:",
  )+

  labs(title = "Disciplinary")+
  ylab("Number of Disciplinary Infractions")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+

    # Set the legend to multiple rows
  guides(col = guide_legend(nrow =8))+
  
  # Wrap
  facet_wrap(~ facility, ncol=3)

6 Sexual Abuse and Assault

6.1 Allegations

6.1.1 Summary Tables

df_sex_alleg <- df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       sexual_abuse_allegations_detainee_on_detainee:
       sexual_abuse_allegations_detainee_on_staff_contractor_volunteer_29
       ) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create a new total column
  mutate(total_sexual_abuse_allegations = sum(c_across(
       sexual_abuse_allegations_detainee_on_detainee:
       sexual_abuse_allegations_detainee_on_staff_contractor_volunteer_29
  ))) %>% 

  # Call a range of table columns and pivot long
  pivot_longer(.,
               cols=  sexual_abuse_allegations_detainee_on_detainee:total_sexual_abuse_allegations,
               names_to = "sexual_abuse_allegations_type",
               values_to = "sexual_abuse_allegations_count") %>%
  
  # Remove NA
  drop_na() %>% 
  
  # Explicitly define factor levels
  mutate(sexual_abuse_allegations_type = factor(sexual_abuse_allegations_type, levels = c(
    "sexual_abuse_allegations_detainee_on_detainee",
    "sexual_abuse_allegations_inmate_on_detainee",
    "sexual_abuse_allegations_detainee_on_inmate",
    "sexual_abuse_allegations_detainee_on_staff_contractor_volunteer",
    "sexual_abuse_allegations_detainee_on_staff_contractor_volunteer_29",
    "total_sexual_abuse_allegations"
  )))

df_sex_alleg %>% 
  group_by(sexual_abuse_allegations_type) %>% 
  summarise(`Sexual Abuse and Assault Allegations by Type` = sum(sexual_abuse_allegations_count)) %>% 
  ungroup() %>% 
  kable(caption = "Total Sexual Abuse and Assault Allegations by Type",
        col.names = c("Allegation Type", "Total Allegation Type")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive"))

Table 6.1: Total Sexual Abuse and Assault Allegations by Type

Allegation Type	Total Allegation Type
sexual_abuse_allegations_detainee_on_detainee	482
sexual_abuse_allegations_inmate_on_detainee	24
sexual_abuse_allegations_detainee_on_inmate	12
sexual_abuse_allegations_detainee_on_staff_contractor_volunteer	175
sexual_abuse_allegations_detainee_on_staff_contractor_volunteer_29	16
total_sexual_abuse_allegations	707

df_sex_alleg %>% 
  group_by(facility) %>% 
  summarise(total_sexual_abuse_allegations = sum(sexual_abuse_allegations_count)) %>% 
  arrange(desc(total_sexual_abuse_allegations)) %>% 
  ungroup() %>% 
  kable(caption = "Total Sexual Abuse and Assault Allegations by Facility",
        col.names = c("Facility", "Total Allegations by Facility")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 6.1: Total Sexual Abuse and Assault Allegations by Facility

Facility	Total Allegations by Facility
Otay Mesa Detention Facility	160
Eloy Detention Center	122
Adelanto ICE Processing Center - West	102
Krome Service Processing Center	70
El Paso Service Processing Center	66
York County Prison	58
Montgomery Processing Center	44
South Texas ICE Processing Center	44
Western Tennessee Detention Facility	36
Imperial Regional Detention Facility	32
Northwest Contract Detention Center	32
Essex County Corrections Facility	24
Irwin County Detention Center	24
Adelanto ICE Processing Center - East	22
Bluebonnet Detention Center	22
Jackson Parish Correctional Center	22
LaSalle ICE Processing Center	22
Otero County Processing Center	22
Folkston ICE Processing Center	20
Clinton County Correctional Facility	18
Dodge County Detention Facility	18
Yuba County Jail	18
Aurora ICE Processing Center	16
Aurora ICE Processing Center II - Annex	16
CCA Florence Correctional Center	16
Hardin County Jail	16
Port Isabel Service Processing Center	16
Webb County Detention Facility	16
Glades County Detention Center	14
Jena LaSalle Detention Facility	14
Okmulgee County Jail - Moore Detention Facility	14
Eden Detention Center	12
Houston CDF	12
La Palma Correctional Center	12
Mesa Verde ICE Processing Facility	12
Prairieland Detention Center	12
Winn Correctional Center	12
Caroline Detention Facility	10
Stewart Detention Center	10
Broward Transitional Center	8
Calhoun County Correctional Center	8
Geauga County Jail	8
Limestone County Detention Center	8
Sherburne County Jail	8
Strafford County Corrections	8
Bergen County Jail	6
Joe Corley Processing Center	6
Northern Oregon Correctional Facility	6
Torrance County Detention Facility	6
Webb County Detention Center	6
Adams County Correctional Center	4
Baker County Detention Center	4
Bristol County Jail and House of Correction	4
El Valle Detention Facility	4
Florence SPC	4
Folkston ICE Processing Center Annex	4
Hall County Department of Corrections	4
Henderson Detention Center	4
Laredo Processing Center	4
McHenry County Adult Correctional Facility	4
Morgan County Adult Detention Center	4
Pine Prairie ICE Processing Center	4
Plymouth County Correctional Facility	4
Rio Grande Processing Center	4
River Correctional Center	4
Seneca County Jail	4
Tulsa County Jail - David L. Moss Criminal Jutice Center	4
Val Verde Correctional Facility	4
Wakulla County Detention Facility	4
Bossier Parish Corrections Center	2
Cass County Jail	2
Cibola County Correctional Center	2
Elizabeth Contract Detention Facility	2
Farmville Detention Center	2
Joe Corley Detention Facility	2
Kay County Detention Center	2
Monroe County Inmate Dormitory	2
Montgomery County Jail	2
Nye County Detention Center	2
Richwood Correctional Center	2
Rolling Plains Detention Center	2
Shawnee County Department of Corrections - Adult Detention Center	2
Sheriff Al Cannon Detention Center	2
South Louisiana ICE Processing Center	2
West Texas Detention Facility	2
Worcester County Jail	2
Alamance County Detention Center	0
Allen Parish Public Safety Complex	0
Boone County Jail	0
Brooks County Detention Center	0
Butler County Jail	0
Cambria County Prison	0
Carver County Jail	0
Catahoula Correctional Center	0
Christian County Jail	0
Clay County Justice Center	0
Coastal Bend Detention Center	0
David L. Moss Criminal Justice Center	0
Donald W. Wyatt Detention Center	0
Douglas County Department of Corrections	0
East Hidalgo Detention Center	0
Essex County Correctional Facility	0
Freeborn County Adult Detention Center	0
Golden State Annex	0
Houston Contract Detention Facility	0
Howard County Detention Center	0
Hudson County Corrections and Rehabilitation Center	0
Jerome Combs Detention Center	0
Johnson County Corrections Center	0
LaSalle Correctional Center	0
LaSalle County Regional Detention Center	0
Morrow County Correctional Facility	0
Orange County Jail	0
Pike County Correctional Facility	0
Platte County Detention Center	0
Polk County Adult Detention Center	0
Pulaski County Detention Center	0
Robert A. Deyton Detention Facility	0
Saint Clair County Jail	0
San Luis Regional Detention Center	0
Teller County Jail	0
Washoe County Detention Center	0
Willacy County Regional Detention Facility	0

6.1.2 Facet Plot of Sexual Abuse and Assault Allegations by Facility

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid",
    "solid",
    "solid",
    "solid",
    "dotted"
    )

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(6, "Paired")
plot_colors[6] <- "#000000"

# Create plot labels
plot_labels <- c(
    "Sexual Abuse Allegations - Detainee on Detainee",
    "Sexual Abuse Allegations - Inmate on Detainee",
    "Sexual Abuse Allegations - Detainee on Inmate",
    "Sexual Abuse Allegations - Staff/Contractor/Volunteer on Detainee",
    "Number of Sexual Abuse Allegations - Detainee on Staff/Contractor/Volunteer",
    "Total Sexual Abuse Allegations")

df_sex_alleg %>% 
  # Calling the plot and formatting
  ggplot(aes(x=date, y = sexual_abuse_allegations_count, linetype=sexual_abuse_allegations_type))+
  geom_line(aes(color = sexual_abuse_allegations_type),size=.65) +
  
  # Set the linetype
  scale_linetype_manual(
    values = plot_lines,
    labels = plot_labels,
    name = "Sexual Abuse Allegation Type:",
    guide = guide_legend(nrow = 6)
    )+
  
  # Set the color
  scale_color_manual(values = plot_colors,
                     labels = plot_labels,
                     name = "Sexual Abuse Allegation Type:")+

  labs(title = "Sexual Abuse Allegations")+
  ylab("Number of Allegations")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+

    # Set the legend to multiple rows
  guides(col = guide_legend(nrow =8))+
  
  # Wrap
  facet_wrap(~ facility, ncol=3)

6.2 Substantiated Allegations

6.2.1 Summary Tables

df_sex_alleg_sub <- df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       sexual_abuse_allegations_detainee_on_detainee_2:
       sexual_abuse_allegations_detainee_on_staff_contractor_volunteer_34
       ) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create a new total column
  mutate(total_sexual_abuse_allegations = sum(c_across(
       sexual_abuse_allegations_detainee_on_detainee_2:
       sexual_abuse_allegations_detainee_on_staff_contractor_volunteer_34
  ))) %>% 

  # Call a range of table columns and pivot long
  pivot_longer(.,
               cols=  sexual_abuse_allegations_detainee_on_detainee_2:total_sexual_abuse_allegations,
               names_to = "sexual_abuse_substantiated_type",
               values_to = "sexual_abuse_substantiated_count") %>%
  
  # Remove NA values
  drop_na() %>% 
  
  # Explicitly set factor levels
  mutate(sexual_abuse_substantiated_type= factor(sexual_abuse_substantiated_type, levels =c(
    "sexual_abuse_allegations_detainee_on_detainee_2",
    "sexual_abuse_allegations_inmate_on_detainee_2",
    "sexual_abuse_allegations_detainee_on_inmate_2",
    "sexual_abuse_allegations_staff_contractor_volunteer_on_detainee",
    "sexual_abuse_allegations_detainee_on_staff_contractor_volunteer_34",
    "total_sexual_abuse_allegations"
  )))

df_sex_alleg_sub %>% 
  group_by(sexual_abuse_substantiated_type) %>% 
  summarise(`Sexual Abuse and Assault Allegations Substantiated by Type` = sum(sexual_abuse_substantiated_count)) %>% 
  ungroup() %>% 
  kable(caption = "Total Substantiated Sexual Abuse and Assault Allegations by Type",
        col.names = c("Substantiated Allegation Type", "Total Substantiated Allegation Type")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive"))

Table 6.2: Total Substantiated Sexual Abuse and Assault Allegations by Type

Substantiated Allegation Type	Total Substantiated Allegation Type
sexual_abuse_allegations_detainee_on_detainee_2	80
sexual_abuse_allegations_inmate_on_detainee_2	10
sexual_abuse_allegations_detainee_on_inmate_2	2
sexual_abuse_allegations_staff_contractor_volunteer_on_detainee	6
sexual_abuse_allegations_detainee_on_staff_contractor_volunteer_34	0
total_sexual_abuse_allegations	98

df_sex_alleg_sub %>% 
  group_by(facility) %>% 
  summarise(total_sexual_abuse_substantiated = sum(sexual_abuse_substantiated_count)) %>% 
  arrange(desc(total_sexual_abuse_substantiated)) %>% 
  ungroup() %>% 
  kable(caption = "Total Substantiated Sexual Abuse and Assault Allegations by Facility",
        col.names = c("Facility", "Total Substantiated Allegations by Facility")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 6.2: Total Substantiated Sexual Abuse and Assault Allegations by Facility

Facility	Total Substantiated Allegations by Facility
Otay Mesa Detention Facility	40
Eloy Detention Center	34
Krome Service Processing Center	26
York County Prison	18
Geauga County Jail	8
Folkston ICE Processing Center	6
Irwin County Detention Center	6
Webb County Detention Facility	6
CCA Florence Correctional Center	4
Morgan County Adult Detention Center	4
Otero County Processing Center	4
Stewart Detention Center	4
Yuba County Jail	4
Bergen County Jail	2
Bluebonnet Detention Center	2
Dodge County Detention Facility	2
El Paso Service Processing Center	2
El Valle Detention Facility	2
Essex County Corrections Facility	2
Hardin County Jail	2
Joe Corley Detention Facility	2
La Palma Correctional Center	2
LaSalle ICE Processing Center	2
Mesa Verde ICE Processing Facility	2
Monroe County Inmate Dormitory	2
Northern Oregon Correctional Facility	2
Okmulgee County Jail - Moore Detention Facility	2
Torrance County Detention Facility	2
Winn Correctional Center	2
Adams County Correctional Center	0
Adelanto ICE Processing Center - East	0
Adelanto ICE Processing Center - West	0
Alamance County Detention Center	0
Allen Parish Public Safety Complex	0
Aurora ICE Processing Center	0
Aurora ICE Processing Center II - Annex	0
Baker County Detention Center	0
Boone County Jail	0
Bossier Parish Corrections Center	0
Bristol County Jail and House of Correction	0
Brooks County Detention Center	0
Broward Transitional Center	0
Butler County Jail	0
Calhoun County Correctional Center	0
Cambria County Prison	0
Caroline Detention Facility	0
Carver County Jail	0
Cass County Jail	0
Catahoula Correctional Center	0
Christian County Jail	0
Cibola County Correctional Center	0
Clay County Justice Center	0
Clinton County Correctional Facility	0
Coastal Bend Detention Center	0
David L. Moss Criminal Justice Center	0
Donald W. Wyatt Detention Center	0
Douglas County Department of Corrections	0
East Hidalgo Detention Center	0
Eden Detention Center	0
Elizabeth Contract Detention Facility	0
Essex County Correctional Facility	0
Farmville Detention Center	0
Florence SPC	0
Folkston ICE Processing Center Annex	0
Freeborn County Adult Detention Center	0
Glades County Detention Center	0
Golden State Annex	0
Hall County Department of Corrections	0
Henderson Detention Center	0
Houston CDF	0
Houston Contract Detention Facility	0
Howard County Detention Center	0
Hudson County Corrections and Rehabilitation Center	0
Imperial Regional Detention Facility	0
Jackson Parish Correctional Center	0
Jena LaSalle Detention Facility	0
Jerome Combs Detention Center	0
Joe Corley Processing Center	0
Johnson County Corrections Center	0
Kay County Detention Center	0
Laredo Processing Center	0
LaSalle Correctional Center	0
LaSalle County Regional Detention Center	0
Limestone County Detention Center	0
McHenry County Adult Correctional Facility	0
Montgomery County Jail	0
Montgomery Processing Center	0
Morrow County Correctional Facility	0
Northwest Contract Detention Center	0
Nye County Detention Center	0
Orange County Jail	0
Pike County Correctional Facility	0
Pine Prairie ICE Processing Center	0
Platte County Detention Center	0
Plymouth County Correctional Facility	0
Polk County Adult Detention Center	0
Port Isabel Service Processing Center	0
Prairieland Detention Center	0
Pulaski County Detention Center	0
Richwood Correctional Center	0
Rio Grande Processing Center	0
River Correctional Center	0
Robert A. Deyton Detention Facility	0
Rolling Plains Detention Center	0
Saint Clair County Jail	0
San Luis Regional Detention Center	0
Seneca County Jail	0
Shawnee County Department of Corrections - Adult Detention Center	0
Sherburne County Jail	0
Sheriff Al Cannon Detention Center	0
South Louisiana ICE Processing Center	0
South Texas ICE Processing Center	0
Strafford County Corrections	0
Teller County Jail	0
Tulsa County Jail - David L. Moss Criminal Jutice Center	0
Val Verde Correctional Facility	0
Wakulla County Detention Facility	0
Washoe County Detention Center	0
Webb County Detention Center	0
West Texas Detention Facility	0
Western Tennessee Detention Facility	0
Willacy County Regional Detention Facility	0

6.2.2 Facet Plot of Substantiated Sexual Abuse and Assault Allegations

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid",
    "solid",
    "solid",
    "solid",
    "dotted"
    )

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(6, "Paired")
plot_colors[6] <- "#000000"

# Create the labels
plot_labels <- c(
    "Sexual Abuse Allegations - Detainee on Detainee",
    "Sexual Abuse Allegations - Inmate on Detainee",
    "Sexual Abuse Allegations - Detainee on Inmate",
    "Sexual Abuse Allegations - Staff/Contractor/Volunteer on Detainee",
    "Number of Sexual Abuse Allegations - Detainee on Staff/Contractor/Volunteer",
    "Total Sexual Abuse Allegations")

df_sex_alleg_sub %>% 
  
  # Calling the plot and formatting
  ggplot(aes(x=date, y = sexual_abuse_substantiated_count, linetype=sexual_abuse_substantiated_type))+
  geom_line(aes(color = sexual_abuse_substantiated_type),size=.65) +
  
  # Set the linetype
  scale_linetype_manual(
    values = plot_lines,
    labels = plot_labels,
    name = "Sexual Abuse Allegation Type:",
    guide = guide_legend(nrow = 6)
    )+
  
  # Set the color
  scale_color_manual(values = plot_colors,
                     labels = plot_labels,
                     name = "Sexual Abuse Allegation Type:")+

  labs(title = "Sexual Abuse Allegations Substantiated")+
  ylab("Number of Allegations")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+

  # Set the legend to multiple rows
  guides(col = guide_legend(nrow =8))+
  
  # Wrap
  facet_wrap(~ facility, ncol=3)

7 Medical

7.1 Medical Observation

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid",
    "dotted"
    )

# Use Color Brewer to set colors
plot_colors <- brewer.pal(3, "Paired")
plot_colors[3] <- "#000000"

# Create plot labels
plot_labels <- c(
    "Detainees in Medical Observation",
    "Detainees in Mental Health Observation",
    "Total Individuals in Medical or Mental Health Observation")

df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       detainees_in_medical_observation:
       detainees_in_mental_health_observation
       ) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create a new total column
  mutate(total_mental_medical_observation = sum(c_across(
       detainees_in_medical_observation:
       detainees_in_mental_health_observation
  ))) %>% 

  # Call a range of table columns and pivot long
  pivot_longer(.,
               cols=  detainees_in_medical_observation:total_mental_medical_observation,
               names_to = "medical_mental_observation_type",
               values_to = "medical_mental_observation_count") %>%
  
  # Remove NA values
  drop_na() %>% 
  
  # Explicitly set factor levels
  mutate(medical_mental_observation_type = factor(medical_mental_observation_type, levels = c(
    "detainees_in_medical_observation",
    "detainees_in_mental_health_observation",
    "total_mental_medical_observation"
  ))) %>% 
  
  # Calling the plot and formatting
  ggplot(aes(x=date, y = medical_mental_observation_count, linetype=medical_mental_observation_type))+
  geom_line(aes(color = medical_mental_observation_type),size=.65) +
  
  # Set the linetype
  scale_linetype_manual(
    values = plot_lines,
    labels = plot_labels,
    name = "Observation Type:",
    guide = guide_legend(nrow = 3)
    )+
  
  # Set the color
  scale_color_manual(values = plot_colors,
                     labels = plot_labels,
                     name = "Observation Type:",)+

  labs(title = "Medical and Mental Health Observation")+
  ylab("Number of Individuals in Observation")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+

  # Set the legend to multiple rows
  guides(col = guide_legend(nrow =3))+
  
  # Wrap
  facet_wrap(~ facility, ncol=3)

7.2 Infections Disease

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid"
    )

# Use Color Brewer to set colors
plot_colors <- brewer.pal(2, "Paired")

# Create plot labels
plot_labels <- c(
    "Infectious Disease Reported",
    "Infectious Disease Confirmed")

df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       infectious_disease_reported:
       infections_disease_confirmed
       ) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # # Create a new total column
  # # In this case not used
  # mutate(total_infections_disease_report_confirmed = sum(c_across(
  #      infectious_disease_reported:
  #      infections_disease_confirmed
  # ))) %>% 

  # Call a range of table columns and pivot long
  pivot_longer(.,
               cols=  infectious_disease_reported:infections_disease_confirmed,
               names_to = "infectious_disease_type",
               values_to = "infectious_disease_count") %>%
  
  # Remove NA values
  drop_na() %>% 
  
  # Explicitly define factor levels
  mutate(infectious_disease_type = factor(infectious_disease_type, levels = c(
    "infectious_disease_reported",
    "infections_disease_confirmed"
  ))) %>% 
  
  # Calling the plot and formatting
  ggplot(aes(x=date, y = infectious_disease_count, linetype=infectious_disease_type))+
  geom_line(aes(color = infectious_disease_type),size=.65) +
  
  # Set the linetype
  scale_linetype_manual(
    values = plot_lines,
    labels = plot_labels,
    name = "Category:",
    guide = guide_legend(nrow = 2)
    )+
  
  # Set the color
  scale_color_manual(values = plot_colors,
    labels = plot_labels,
    name = "Category:")+

  labs(title = "Infectious Diseases Reported and Confirmed")+
  ylab("Count")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+

  # Set the legend to multiple rows
  guides(col = guide_legend(nrow =3))+
  
  # Wrap
  facet_wrap(~ facility, ncol=3)

7.3 Medical and Mental Health Referrals

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid",
    "solid",
    "solid",
    "dotted"
    )

# Use Color Brewer to set colors
plot_colors <- brewer.pal(5, "Paired")
plot_colors[5] <- "#000000"

# Create plot labels
plot_labels <- c(
    "Outside Medical Referrals",
    "Detainees Transported to Off-Site Hospitals for Emergency Reasons",
    "Admissions to Off-Site Hospitals for Medical Reasons",
    "Admissions to Off-Site Hospitals for Mental Health Reasons",
    "Total Referrals")


df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       outside_medical_referrals:
       admissions_to_off_site_hospitals_for_mental_health_reasons
       ) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create a new total column
  mutate(total_referrals = sum(c_across(
       outside_medical_referrals:
       admissions_to_off_site_hospitals_for_mental_health_reasons
  ))) %>% 

  # Call a range of table columns and pivot long
  pivot_longer(.,
               cols=  outside_medical_referrals:total_referrals,
               names_to = "referral_type",
               values_to = "referral_count") %>%
  
  # Remove NA values
  drop_na() %>% 
  
  # Explicitly define factor levels
  mutate(referral_type= factor(referral_type, levels = c(
    "outside_medical_referrals",
    "detainees_transported_to_off_site_hospitals_for_emergency_care",
    "admissions_to_off_site_hospitals_for_medical_reasons",
    "admissions_to_off_site_hospitals_for_mental_health_reasons",
    "total_referrals"
  ))) %>% 
  
  
  # Calling the plot and formatting
  ggplot(aes(x=date, y = referral_count, linetype=referral_type))+
  geom_line(aes(color = referral_type),size=.65) +
  
  # Set the linetype
  scale_linetype_manual(
    values = plot_lines,
    labels = plot_labels,
    name = "Referral Type:",
    guide = guide_legend(nrow = 5)
    )+
  
  # Set the color
  scale_color_manual(values = plot_colors,
    labels = plot_labels,
    name = "Referral Type:")+

  labs(title = "Medical and Mental Health Referrals")+
  ylab("Number of Referrals")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+

  # Set the legend to multiple rows
  guides(col = guide_legend(nrow =5))+
  
  # Wrap
  facet_wrap(~ facility, ncol=3)

7.4 Sick Call Requests and Encounters

df_sick_call <- df_324_inc %>%
  
  # Select a subset of columns to work with
  select(id,
         facility,
         date,
         sick_call_requests,
         sick_call_encounters) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create new total column
  mutate(total_sick_call = sick_call_requests,
         sick_call_encounters) %>% 
  
  # Tidy
  pivot_longer(.,
               cols= sick_call_requests:
         sick_call_encounters,
               names_to = "sick_call_type",
               values_to = "sick_call_count") %>% 
  
  # Remove NA
  drop_na() %>% 
  
  # Explicitly set factor levels
  mutate(sick_call_type = factor(sick_call_type, levels = c(
    "sick_call_requests",
    "sick_call_encounters",
    "total_sick_call"
  )))

df_sick_call %>% 
  group_by(sick_call_type) %>% 
  summarise(`Total Sick Call by Type` = sum(sick_call_count)) %>% 
  ungroup() %>% 
  kable(caption = "Total Sick Call by Type",
        col.names = c("Type", "Total")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive"))

Table 7.1: Total Sick Call by Type

Type	Total
sick_call_requests	617349
sick_call_encounters	607870

df_sick_call %>% 
  group_by(facility) %>% 
  summarise(total_sick_call = sum(sick_call_count)) %>% 
  arrange(desc(total_sick_call)) %>% 
  ungroup() %>% 
  kable(caption = "Total Sick Call Requests/Encounters by Facility",
        col.names = c("Facility", "Total")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 7.1: Total Sick Call Requests/Encounters by Facility

Facility	Total
Adelanto ICE Processing Center - East	66777
Adelanto ICE Processing Center - West	66777
Port Isabel Service Processing Center	59808
South Texas ICE Processing Center	48814
Montgomery Processing Center	44111
Rio Grande Processing Center	44102
Otay Mesa Detention Facility	42973
Eloy Detention Center	39798
Prairieland Detention Center	36952
Otero County Processing Center	30388
Imperial Regional Detention Facility	30196
Broward Transitional Center	30028
Polk County Adult Detention Center	29048
El Paso Service Processing Center	28326
Henderson Detention Center	27056
Jackson Parish Correctional Center	26363
River Correctional Center	25976
Irwin County Detention Center	23626
Aurora ICE Processing Center	23178
Aurora ICE Processing Center II - Annex	23178
Krome Service Processing Center	23057
Essex County Corrections Facility	21902
Stewart Detention Center	20457
El Valle Detention Facility	19821
Winn Correctional Center	19786
Houston CDF	17439
LaSalle ICE Processing Center	16400
La Palma Correctional Center	16032
Adams County Correctional Center	16025
Farmville Detention Center	15811
York County Prison	14910
Jena LaSalle Detention Facility	14429
Webb County Detention Center	13191
Bossier Parish Corrections Center	12884
Elizabeth Contract Detention Facility	11870
Catahoula Correctional Center	11612
Sherburne County Jail	11064
Joe Corley Detention Facility	10367
Mesa Verde ICE Processing Facility	10336
Folkston ICE Processing Center	9572
McHenry County Adult Correctional Facility	9245
Calhoun County Correctional Center	9010
Webb County Detention Facility	8494
Florence SPC	8363
Laredo Processing Center	8351
Pine Prairie ICE Processing Center	7906
Torrance County Detention Facility	7766
South Louisiana ICE Processing Center	7608
Houston Contract Detention Facility	6421
Joe Corley Processing Center	6389
Bluebonnet Detention Center	6309
Caroline Detention Facility	5244
Richwood Correctional Center	4210
Orange County Jail	3948
Hudson County Corrections and Rehabilitation Center	3941
Folkston ICE Processing Center Annex	3778
Donald W. Wyatt Detention Center	3738
Johnson County Corrections Center	3628
Okmulgee County Jail - Moore Detention Facility	3524
Yuba County Jail	3432
Geauga County Jail	3299
Baker County Detention Center	3263
Wakulla County Detention Facility	3161
Allen Parish Public Safety Complex	3052
Pike County Correctional Facility	2964
CCA Florence Correctional Center	2830
Pulaski County Detention Center	2644
Clinton County Correctional Facility	2416
Limestone County Detention Center	2334
Tulsa County Jail - David L. Moss Criminal Jutice Center	2174
Kay County Detention Center	2026
Bristol County Jail and House of Correction	2006
Carver County Jail	1940
Hardin County Jail	1688
Butler County Jail	1174
Clay County Justice Center	1115
Worcester County Jail	1060
Bergen County Jail	986
Jerome Combs Detention Center	908
Morgan County Adult Detention Center	876
Cambria County Prison	742
Montgomery County Jail	658
Val Verde Correctional Facility	649
LaSalle Correctional Center	546
Howard County Detention Center	526
Strafford County Corrections	507
Freeborn County Adult Detention Center	472
Rolling Plains Detention Center	456
Northern Oregon Correctional Facility	414
Alamance County Detention Center	360
West Texas Detention Facility	334
Saint Clair County Jail	320
Coastal Bend Detention Center	296
Cibola County Correctional Center	259
Morrow County Correctional Facility	184
Teller County Jail	164
Platte County Detention Center	156
Golden State Annex	140
Shawnee County Department of Corrections - Adult Detention Center	132
Seneca County Jail	105
LaSalle County Regional Detention Center	62
Christian County Jail	24
Brooks County Detention Center	21
San Luis Regional Detention Center	17
Washoe County Detention Center	14
David L. Moss Criminal Justice Center	0
East Hidalgo Detention Center	0
Eden Detention Center	0
Nye County Detention Center	0
Robert A. Deyton Detention Facility	0
Sheriff Al Cannon Detention Center	0
Western Tennessee Detention Facility	0
Willacy County Regional Detention Facility	0

# Generating a linetype vector for use in the plot
plot_lines <- c(
    "solid",
    "solid",
    "dotted"
    )

# Use Color Brewer to set colors
plot_colors <- brewer.pal(3, "Paired")
plot_colors[3] <- "#000000"

# Create labels
plot_labels <- c(
    "Sick Call Requests",
    "Sick Call Encounters",
    "Total Sick Calls")

df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       sick_call_requests:
       sick_call_encounters
       ) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create a new total column
  mutate(total_sick_calls = sum(c_across(
       sick_call_requests:
       sick_call_encounters
  ))) %>% 

  # Call a range of table columns and pivot long
  pivot_longer(.,
               cols=  sick_call_requests:total_sick_calls,
               names_to = "sick_call_type",
               values_to = "sick_call_count") %>%
  
  # Remove NA values
  drop_na() %>% 
  
  # Explicitly define factor levels
  mutate(sick_call_type = factor(sick_call_type, levels = c(
    "sick_call_requests",
    "sick_call_encounters",
    "total_sick_calls"
  ))) %>% 
  
  # Calling the plot and formatting
  ggplot(aes(x=date, y = sick_call_count, linetype=sick_call_type))+
  geom_line(aes(color = sick_call_type),size=.65) +
  
  # Set the linetype
  scale_linetype_manual(
    values = plot_lines,
    labels = plot_labels,
    name = "Sick Call Type:",
    guide = guide_legend(nrow = 3)
    )+
  
  # Set the color
  scale_color_manual(values = plot_colors,
    labels = plot_labels,
    name = "Sick Call Type:")+

  labs(title = "Sick Calls")+
  ylab("Number of Sick Calls")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 8),
    legend.position = "bottom"
    )+

  # Set the legend to multiple rows
  guides(col = guide_legend(nrow =3))+
  
  # Wrap
  facet_wrap(~ facility, ncol=3)

7.5 Suicide Attempts and Watches

The following shows Suicide Attempts and Suicide Watches based on the status of the data as of 2021-06-24. The numbers are subject to change.

df_suicide <- df_324_inc %>%
  
  # Select a subset of columns to work with
  select(id,
         facility,
         date,
         suicide_attempts_or_self_harm,
         suicide_watches_constant_watch_mental_health_observation) %>% 
  
  # Need the rowwise function to compute a row-at-a-time
  # in the following mutate function
  rowwise(id) %>% 
  
  # Create new total column
  mutate(total_suicide = suicide_attempts_or_self_harm +
         suicide_watches_constant_watch_mental_health_observation) %>% 
  
  # Tidy
  pivot_longer(.,
               cols= suicide_attempts_or_self_harm:
               total_suicide,
               names_to = "suicide_type",
               values_to = "suicide_count") %>% 
  
  # Remove NA
  drop_na() %>% 
  
  # Explicitly set factor levels
  mutate(segregation_type = factor(suicide_type, levels = c(
    "suicide_attempts_or_self_harm",
    "suicide_watches_constant_watch_mental_health_observation",
    "total_suicide"
  )))

df_suicide %>% 
  group_by(suicide_type) %>% 
  summarise(`Total Suicide Attempt or Watch by Type` = sum(suicide_count)) %>% 
  ungroup() %>% 
  kable(caption = "Total Suicide Attempt or Watch by Type",
        col.names = c("Type", "Total")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive"))

Table 7.2: Total Suicide Attempt or Watch by Type

Type	Total
suicide_attempts_or_self_harm	234
suicide_watches_constant_watch_mental_health_observation	4716
total_suicide	4948

df_suicide %>% 
  group_by(facility) %>% 
  summarise(total_suicide = sum(suicide_count)) %>% 
  arrange(desc(total_suicide)) %>% 
  ungroup() %>% 
  kable(caption = "Total Suicide Attempt or Watch by Facility",
        col.names = c("Facility", "Total")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 7.2: Total Suicide Attempt or Watch by Facility

Facility	Total
Adelanto ICE Processing Center - East	878
Adelanto ICE Processing Center - West	878
Henderson Detention Center	750
Aurora ICE Processing Center	606
Aurora ICE Processing Center II - Annex	606
La Palma Correctional Center	402
Bristol County Jail and House of Correction	390
Port Isabel Service Processing Center	358
Otay Mesa Detention Facility	282
Eloy Detention Center	246
York County Prison	214
Stewart Detention Center	200
Otero County Processing Center	192
Montgomery Processing Center	182
Irwin County Detention Center	178
Prairieland Detention Center	158
South Texas ICE Processing Center	158
Imperial Regional Detention Facility	134
Pike County Correctional Facility	132
Folkston ICE Processing Center	122
Polk County Adult Detention Center	114
Essex County Corrections Facility	112
Bergen County Jail	108
Glades County Detention Center	102
LaSalle ICE Processing Center	102
Nye County Detention Center	102
River Correctional Center	92
Winn Correctional Center	92
El Valle Detention Facility	86
Farmville Detention Center	86
El Paso Service Processing Center	84
Krome Service Processing Center	74
Sherburne County Jail	74
Florence SPC	70
Jena LaSalle Detention Facility	68
Broward Transitional Center	64
Adams County Correctional Center	62
Caroline Detention Facility	60
Limestone County Detention Center	56
Carver County Jail	54
Mesa Verde ICE Processing Facility	52
Elizabeth Contract Detention Facility	50
Jackson Parish Correctional Center	46
Essex County Correctional Facility	44
Joe Corley Detention Facility	44
Plymouth County Correctional Facility	42
Pine Prairie ICE Processing Center	40
Webb County Detention Facility	40
CCA Florence Correctional Center	36
Houston CDF	36
Pulaski County Detention Center	34
Houston Contract Detention Facility	32
McHenry County Adult Correctional Facility	32
Strafford County Corrections	32
South Louisiana ICE Processing Center	30
Tulsa County Jail - David L. Moss Criminal Jutice Center	30
Folkston ICE Processing Center Annex	24
Hudson County Corrections and Rehabilitation Center	24
Yuba County Jail	24
Baker County Detention Center	22
Butler County Jail	22
Calhoun County Correctional Center	22
Rio Grande Processing Center	22
Torrance County Detention Facility	22
Worcester County Jail	22
Joe Corley Processing Center	20
Johnson County Corrections Center	20
Shawnee County Department of Corrections - Adult Detention Center	20
Bluebonnet Detention Center	18
Allen Parish Public Safety Complex	16
Catahoula Correctional Center	16
Clinton County Correctional Facility	16
Donald W. Wyatt Detention Center	14
Kay County Detention Center	14
Alamance County Detention Center	12
Boone County Jail	12
Orange County Jail	12
Val Verde Correctional Facility	12
Wakulla County Detention Facility	12
Bossier Parish Corrections Center	10
Howard County Detention Center	10
Okmulgee County Jail - Moore Detention Facility	10
Seneca County Jail	10
Dodge County Detention Facility	8
Geauga County Jail	8
Richwood Correctional Center	8
Robert A. Deyton Detention Facility	8
Webb County Detention Center	8
Coastal Bend Detention Center	6
Laredo Processing Center	6
San Luis Regional Detention Center	6
Sheriff Al Cannon Detention Center	6
Clay County Justice Center	4
Hardin County Jail	4
LaSalle Correctional Center	4
Morgan County Adult Detention Center	4
Cambria County Prison	2
Freeborn County Adult Detention Center	2
Hall County Department of Corrections	2
Jerome Combs Detention Center	2
Northern Oregon Correctional Facility	2
West Texas Detention Facility	2
Brooks County Detention Center	0
Cass County Jail	0
Christian County Jail	0
Cibola County Correctional Center	0
David L. Moss Criminal Justice Center	0
East Hidalgo Detention Center	0
Eden Detention Center	0
Golden State Annex	0
LaSalle County Regional Detention Center	0
Monroe County Inmate Dormitory	0
Montgomery County Jail	0
Morrow County Correctional Facility	0
Platte County Detention Center	0
Rolling Plains Detention Center	0
Saint Clair County Jail	0
Teller County Jail	0
Washoe County Detention Center	0
Western Tennessee Detention Facility	0
Willacy County Regional Detention Facility	0

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(2, "Paired")

# Create plot labels
plot_labels <- c(
      "Suicide Attempts or Self Harm",
      "Suicide Watches/Constant Watch/Mental Health Observation")

df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       suicide_attempts_or_self_harm,
       suicide_watches_constant_watch_mental_health_observation
       ) %>% 
  drop_na() %>% 
 
  # Call a range of table columns and pivot long
  pivot_longer(.,
               cols=  c(suicide_attempts_or_self_harm,
       suicide_watches_constant_watch_mental_health_observation),
               names_to = "suicide_type",
               values_to = "suicide_count") %>% 
  
  # Remove NA values
  drop_na() %>% 
  
  # Explicitly define factor levels
  mutate(suicide_type = factor(suicide_type, levels = c(
    "suicide_attempts_or_self_harm",
    "suicide_watches_constant_watch_mental_health_observation"
  ))) %>% 
  
  # Calling the plot and formatting
  ggplot(aes(x=date, y = suicide_count))+
  geom_line(aes(color=suicide_type), size = .65) +
  
  # Set the color
  scale_color_manual(
    values = plot_colors,
    labels = plot_labels,
    name = "Type:"
    )+
  
  labs(title = "Suicide Attempts and Watches")+
  ylab("Number of Attempts or Watches")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 5),
    legend.position = "bottom"
    )+
  # Set the legend to multiple rows
  guides(col = guide_legend(nrow =5))+
  
  # Wrap
  facet_wrap(~ facility, ncol = 3)

7.6 Hunger Strikes

df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date, hunger_strikes) %>% 

  group_by(facility) %>% 
  summarise(total_hunger_strike = sum(hunger_strikes)) %>% 
  arrange(desc(total_hunger_strike)) %>% 
  ungroup() %>% 
  kable(caption = "Total Hunger Strikes by Facility",
        col.names = c("Facility", "Total Hunger Strikes")) %>% 
  kable_styling(c("hover", "striped", "condensed", "responsive")) %>% 
  scroll_box(height = "300px")

Table 7.3: Total Hunger Strikes by Facility

Facility	Total Hunger Strikes
Bossier Parish Corrections Center	136
Krome Service Processing Center	71
La Palma Correctional Center	62
LaSalle ICE Processing Center	53
Otero County Processing Center	51
Jena LaSalle Detention Facility	49
Otay Mesa Detention Facility	48
Bristol County Jail and House of Correction	47
El Paso Service Processing Center	46
Pine Prairie ICE Processing Center	42
Port Isabel Service Processing Center	35
Adelanto ICE Processing Center - East	28
Adelanto ICE Processing Center - West	28
Montgomery Processing Center	18
Prairieland Detention Center	17
Irwin County Detention Center	14
Okmulgee County Jail - Moore Detention Facility	14
Johnson County Corrections Center	13
Imperial Regional Detention Facility	11
South Texas ICE Processing Center	11
Stewart Detention Center	11
Florence SPC	8
Butler County Jail	7
Teller County Jail	7
Farmville Detention Center	6
Houston Contract Detention Facility	6
Elizabeth Contract Detention Facility	5
Folkston ICE Processing Center	5
Plymouth County Correctional Facility	5
Sherburne County Jail	5
Torrance County Detention Facility	5
Cibola County Correctional Center	4
Tulsa County Jail - David L. Moss Criminal Jutice Center	4
Henderson Detention Center	3
Joe Corley Processing Center	3
York County Prison	3
Baker County Detention Center	2
McHenry County Adult Correctional Facility	2
Nye County Detention Center	2
Pike County Correctional Facility	2
Polk County Adult Detention Center	2
Wakulla County Detention Facility	2
Broward Transitional Center	1
Cambria County Prison	1
Caroline Detention Facility	1
Catahoula Correctional Center	1
CCA Florence Correctional Center	1
Clinton County Correctional Facility	1
El Valle Detention Facility	1
Houston CDF	1
Hudson County Corrections and Rehabilitation Center	1
Joe Corley Detention Facility	1
Northern Oregon Correctional Facility	1
San Luis Regional Detention Center	1
Alamance County Detention Center	0
Bergen County Jail	0
Brooks County Detention Center	0
Calhoun County Correctional Center	0
Carver County Jail	0
Cass County Jail	0
Christian County Jail	0
Clay County Justice Center	0
Coastal Bend Detention Center	0
David L. Moss Criminal Justice Center	0
Dodge County Detention Facility	0
Donald W. Wyatt Detention Center	0
Douglas County Department of Corrections	0
East Hidalgo Detention Center	0
Eden Detention Center	0
Essex County Correctional Facility	0
Essex County Corrections Facility	0
Folkston ICE Processing Center Annex	0
Glades County Detention Center	0
Golden State Annex	0
Hall County Department of Corrections	0
Hardin County Jail	0
Laredo Processing Center	0
Limestone County Detention Center	0
Mesa Verde ICE Processing Facility	0
Montgomery County Jail	0
Morgan County Adult Detention Center	0
Morrow County Correctional Facility	0
Orange County Jail	0
Platte County Detention Center	0
Pulaski County Detention Center	0
Rio Grande Processing Center	0
Robert A. Deyton Detention Facility	0
Rolling Plains Detention Center	0
Saint Clair County Jail	0
Seneca County Jail	0
Shawnee County Department of Corrections - Adult Detention Center	0
Sheriff Al Cannon Detention Center	0
Strafford County Corrections	0
Val Verde Correctional Facility	0
Washoe County Detention Center	0
Webb County Detention Center	0
Webb County Detention Facility	0
West Texas Detention Facility	0
Western Tennessee Detention Facility	0
Willacy County Regional Detention Facility	0
Worcester County Jail	0
Adams County Correctional Center	NA
Alamance County Jail	NA
Allen Parish Public Safety Complex	NA
Aurora ICE Processing Center	NA
Aurora ICE Processing Center II - Annex	NA
Bluebonnet Detention Center	NA
Boone County Jail	NA
Calhoun County Jail	NA
Chase County Detention Center	NA
Chippewa County Correctional Facility	NA
Desert View Annex	NA
Donald W. Wyatt Detention Facility	NA
Dorchester County Detention Center	NA
Eloy Detention Center	NA
Freeborn County Adult Detention Center	NA
Geauga County Jail	NA
Howard County Detention Center	NA
Jackson Parish Correctional Center	NA
Jerome Combs Detention Center	NA
Kay County Detention Center	NA
LaSalle Correctional Center	NA
LaSalle County Regional Detention Center	NA
Monroe County Inmate Dormitory	NA
Northwest Contract Detention Center	NA
Richwood Correctional Center	NA
River Correctional Center	NA
South Louisiana ICE Processing Center	NA
Winn Correctional Center	NA
Yuba County Jail	NA

# Use Color Brewer to set colors and modify
# the last color to be black for totals.
plot_colors <- brewer.pal(2, "Paired")

df_324_inc %>%
  
  # Subset the df to only the used cols
  select(id, facility, date,
       hunger_strikes
       ) %>% 
  drop_na() %>% 
 

  # Calling the plot and formatting
  ggplot(aes(x=date, y = hunger_strikes))+
  geom_line(size = .65) +
  
  # scale_color_manual(
  #   values = plot_colors,
  #   labels = c(
  #     "Suicide Attempts or Self Harm",
  #     "Suicide Watches/Constant Watch/Mental Health Observation"
  #     ),
  #   name = "Type:"
  #   )+
  # 
  labs(title = "Hunger Strikes")+
  ylab("Number of Hunger Strikes")+
  xlab("Date")+
  theme(
    strip.text = element_text(size = 5),
    legend.position = "bottom"
    )+
  
  # Set the legend to multiple rows
  guides(col = guide_legend(nrow =5))+
  
  # Wrap
  facet_wrap(~ facility, ncol = 3)

8 Cause of Death

8.1 Suicide as Cause of Death

Bar plot of ICE and non-ICE deaths by suicide plotted by facility as of 2021-06-24.

df_324 %>% 
  select(id,
         facility,
         state,
         date,
         fac_operator,
         cod_suicide_ice,
         cod_suicide_not_ice) %>% 
  drop_na() %>% 
  filter(cod_suicide_ice>0|cod_suicide_not_ice >0) %>% 
  mutate(cod_suicide_total = cod_suicide_ice + cod_suicide_not_ice) %>% 
  
  # Here one could call datatable() or kable()
  # to get a list of the facilities and count
  
  # Initiate the plot
  ggplot(aes(x=cod_suicide_total, y=facility))+
  geom_boxplot()+
  scale_x_continuous(breaks = c(1,2))+
  labs(title = "Cause of Death Suicide",
       subtitle = "Includes ICE and non-ICE Deaths by Suicide")+
  xlab("COD Suicide Total")+
  ylab("Facility")

9 Observations

Observations made on the data as they accumulate are logged below.

9.1 28 May 2021

1. Adelanto ICE Processing Center - East and West have identical data for 2020, but the numbers are different for 2019 with East being much lower than west. Craig checked the inspections and the numbers are different for East and West in 2019 while they are in fact the same for 2020. Note that 2020 is a remote inspection. However, it is significant that the two are comparable in one instance and not comparable in another case.

2. Almance County Jail and Chase County Detention Center both seem to register blank for solitary. Craig suspects this is because there were not cases of solitary reported.

9.2 27 May 2021

One of the important early observations has to do with the naming of facilities. ICE is often inconsistent with facility naming and the names do often change over time. Both the changing of names and inconsistent naming conventions can cause confusion as well as error when tabulating results.

1. The graphs for “Adelanto ICE Processing Center - East” and “Adelanto ICE Processing Center - West” are identical. This is consistent with information Craig recalls seeing in one of the inspections, that the numbers for the facilities are “merged” or combined.

   • For facet graphing consider filtering. For analysis purposes may need to treat the two facilities as “merged”

2. “Adelanto ICE Processing Center West” should be combined with “Adelanto ICE Processing Center - West.” It appears that ICE is not consistently naming the facilities, in one case the name lacks a dash character which causes them to be graphed separately.

   • The dash was added to Adelanto West.

3. It would be good to check if there really two facilities in Almance County. There are entries listed for “Almance County Detention Center” and “Almance County Jail.”

   • Need to verify that these are in fact distinct facilities.

4. “Aurora ICE Processing Center II - Annex” and “Aurora II Annex” should probably be combined. Need to check the inspections to verify.

   • “Aurora II Annex (CO) - Jan. 29, 2021" was changed to”Aurora ICE Processing Center II - Annex (CO) - Jan. 29, 2021"

10 References

Bryan, Jennifer. 2021. Googlesheets4: Access Google Sheets Using the Sheets API V4. https://github.com/tidyverse/googlesheets4.

MA AG. 2020. “Investigation into the Events of May 1, 2020 at the c. Carlos Carreiro Immigration Detention Center, Unit b, Bristol County Sheriff’s Office.” Boston, MA. https://www.mass.gov/doc/ago-report-into-bcso-response-to-may-1-disturbance/download.

Spinu, Vitalie, Garrett Grolemund, and Hadley Wickham. 2021. Lubridate: Make Dealing with Dates a Little Easier. https://CRAN.R-project.org/package=lubridate.

Swetlitz, Ike. 2020. “’Suddenly They Started Gassing Us’: Cuban Migrants Tell of Shocking Attack at ICE Prison.” https://www.theguardian.com/us-news/2020/jul/02/cuban-migrants-detention-ice-facility-new-mexico.

Tukey, John Wilder. 1977. Exploratory Data Analysis. Addison-Wesley Series in Behavioral Science. Reading, Mass: Addison-Wesley Pub. Co.

Wickham, Hadley, Winston Chang, Lionel Henry, Thomas Lin Pedersen, Kohske Takahashi, Claus Wilke, Kara Woo, Hiroaki Yutani, and Dewey Dunnington. 2021. Ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics. https://CRAN.R-project.org/package=ggplot2.

Wickham, Hadley, and Jim Hester. 2020. Readr: Read Rectangular Text Data. https://CRAN.R-project.org/package=readr.